geoskill-urban-canyon-analysis

Compute street canyon height-to-width ratio and sky view factor (SVF) from a digital surface model.

城市峡谷分析 | Urban Canyon Analysis

Derives street canyon morphological parameters from a digital surface model (DSM), for urban climate, thermal environment and radiation studies.

Core algorithm: building height = DSM − DTM (when no DTM is available, the ground surface is estimated with morphological opening); street width is estimated from the Euclidean distance transform of non-building areas (centerline width ≈ 2 × distance to the nearest building); H/W ratio = height/width; the sky view factor adopts the analytical solution for a two-dimensional canyon, SVF = 1/sqrt(1+(H/W)²), in the range [0,1] — open areas take 1, deep canyons tend to 0.

Dependencies / 依赖

bash

pip install 'numpy' 'rasterio' 'scipy'

Usage / 使用方法

Basic Usage

bash

python geoskill-urban-canyon-analysis.py --bbox 116.0 39.0 117.0 40.0 [other parameters]

Examples

Example 1 (Synthetic Data (Offline))

bash

python geoskill-urban-canyon-analysis.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out

Example 2 (Usage 2)

bash

python geoskill-urban-canyon-analysis.py --input dsm.tif --dtm dtm.tif --output-dir ./out

Example 3 (Usage 3)

bash

python geoskill-urban-canyon-analysis.py --bbox 121.0 31.0 122.0 32.0 --threshold 3.0 --output-dir ./out --quiet

Example 4 (Usage 4)

bash

python geoskill-urban-canyon-analysis.py --input dsm.tif --threshold 1.5 --output-dir ./out

Example 5 (Usage 5)

bash

python geoskill-urban-canyon-analysis.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out --quiet

Output / 输出

File	Format	Description
urban_canyon.tif	GeoTIFF	Three bands: band1=building height, band2=H/W ratio, band3=SVF
canyon_stats.json	JSON	Mean street H/W, mean SVF, SVF range
output-manifest.json	JSON	Run manifest

Data Source / 数据源 / Source

Local DSM GeoTIFF (+ optional DTM); --synthetic mode generates an offline scene of a regular block grid (building blocks + straight streets).

Privacy / 隐私声明 / Privacy

• Runs offline by default; --synthetic mode requires no network at all.
• All processing is done locally; user data is never uploaded.

License / License

MIT

---

---

name: geoskill-urban-canyon-analysis description: 'Compute street canyon height-to-width ratio and sky view factor (SVF) from a digital surface model.'

城市峡谷分析 | Urban Canyon Analysis

从数字表面模型（DSM）推导街道峡谷形态参数，用于城市气候、热环境与辐射研究。

核心算法：建筑高度 = DSM − DTM（无 DTM 时用形态学开运算估计地面）；街道宽度由非建筑区欧氏距离变换估计（中心线宽度 ≈ 2×到最近建筑距离）；H/W 比 = 高度/宽度；天空可视因子取二维峡谷解析解 SVF = 1/sqrt(1+(H/W)²)，值域 [0,1]，开阔地为 1、深峡谷趋于 0。

依赖

bash

pip install 'numpy' 'rasterio' 'scipy'

使用方法

基本用法

bash

python geoskill-urban-canyon-analysis.py --bbox 116.0 39.0 117.0 40.0 [其他参数]

示例

示例 1（合成数据（离线））

bash

python geoskill-urban-canyon-analysis.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out

示例 2（用法 2）

bash

python geoskill-urban-canyon-analysis.py --input dsm.tif --dtm dtm.tif --output-dir ./out

示例 3（用法 3）

bash

python geoskill-urban-canyon-analysis.py --bbox 121.0 31.0 122.0 32.0 --threshold 3.0 --output-dir ./out --quiet

示例 4（用法 4）

bash

python geoskill-urban-canyon-analysis.py --input dsm.tif --threshold 1.5 --output-dir ./out

示例 5（用法 5）

bash

python geoskill-urban-canyon-analysis.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out --quiet

输出

文件	格式	说明
urban_canyon.tif	GeoTIFF	三波段：band1=建筑高度，band2=H/W 比，band3=SVF
canyon_stats.json	JSON	街道平均 H/W、平均 SVF、SVF 范围
output-manifest.json	JSON	运行清单

数据源 / Source

本地 DSM GeoTIFF（+ 可选 DTM）；--synthetic 模式生成规则街区网格（建筑块 + 直街道）的离线场景。

隐私声明 / Privacy

• 默认离线运行，--synthetic 模式完全无网络。
• 所有处理在本地完成，不上传用户数据。

License

MIT